Analytical modelling for residual stress prediction in multi-step side milling of GH4169 thin-wall parts based on deformation

GH4169 thin-walled parts are widely used in aerospace due to their high-temperature, corrosion resistance, and fatigue strength. However, they often deform from machining-induced residual stress, which is a significant unresolved manufacturing challenge. Additionally, initial residual stress from previous steps critically impacts subsequent processes. This study found that the residual stress of side milling of thin-walled parts under smaller cutting parameters is mainly caused by mechanical effects, and the influence of milling heat can be ignored. In this study, an analytical prediction model for residual stress of multi-step side milling thin-walled parts based on the deformation of thin-walled parts is proposed for the first time, which is suitable for smaller cutting parameters. Then, the proposed model is examined the mechanisms through which residual stresses develop during side milling and defined the applicability of model based on specific assumptions. To validate these assumptions, an experimental setup was devloped to simulate the movement of the heat source during milling. Subsequent two-step side milling experiments on GH4169 confirmed the accuracy of the analytical prediction model in predicting the residual stresses of multi-step side milling in thin-walled parts. It was observed that higher equivalent bending stiffness in thin-walled parts correlates with reduced machining deformation. The analytical model also provides a strategic approach to control machining deformation by managing the equivalent bending stiffness of the parts.

Authors

Institutions

Publication Details

Journal
Journal of Materials Research and Technology
Published
2024-08-13
DOI
https://doi.org/10.1016/j.jmrt.2024.08.042
Citations
11
Primary Topic
Advanced machining processes and optimization
Type
article
Field-Weighted Citation Impact
2.34

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analytical modelling for residual stress prediction in multi-step side milling of GH4169 thin-wall parts based on deformation

Gonghou Yao, Zhanqiang Liu
11 citations
Journal of Materials Research and Technology
Advanced machining processes and optimization
2.34
article

Analytical modelling for residual stress prediction in multi-step side milling of GH4169 thin-wall parts based on deformation

Gonghou Yao, Zhanqiang Liu
article en
11 citations

Abstract

GH4169 thin-walled parts are widely used in aerospace due to their high-temperature, corrosion resistance, and fatigue strength. However, they often deform from machining-induced residual stress, which is a significant unresolved manufacturing challenge. Additionally, initial residual stress from previous steps critically impacts subsequent processes. This study found that the residual stress of side milling of thin-walled parts under smaller cutting parameters is mainly caused by mechanical effects, and the influence of milling heat can be ignored. In this study, an analytical prediction model for residual stress of multi-step side milling thin-walled parts based on the deformation of thin-walled parts is proposed for the first time, which is suitable for smaller cutting parameters. Then, the proposed model is examined the mechanisms through which residual stresses develop during side milling and defined the applicability of model based on specific assumptions. To validate these assumptions, an experimental setup was devloped to simulate the movement of the heat source during milling. Subsequent two-step side milling experiments on GH4169 confirmed the accuracy of the analytical prediction model in predicting the residual stresses of multi-step side milling in thin-walled parts. It was observed that higher equivalent bending stiffness in thin-walled parts correlates with reduced machining deformation. The analytical model also provides a strategic approach to control machining deformation by managing the equivalent bending stiffness of the parts.

Journal of Materials Research and TechnologyVol. 32
Ministry of Education of the People's Republic of China (CN), Shandong University (CN), Ministry of Education (ME)
National Natural Science Foundation of China
Climate action
Openalex Percentile: Top 12%
Advanced machining processes and optimization
2.34
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.